Chapter 8: Q. 8.24 (page 392)
Itis a Poisson random variable with a mean, thenis approximately
or
Short Answer
Then,is approximately
Chapter 8: Q. 8.24 (page 392)
Itis a Poisson random variable with a mean, thenis approximately
or
Then,is approximately
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Get started for freeA clinic is equally likely to have 2, 3, or 4 doctors volunteer for service on a given day. No matter how many volunteer doctors there are on a given day, the numbers of patients seen by these doctors are independent Poisson random variables with a mean of . Let X denote the number of patients seen in the clinic on a given day.
(a) Find
(b) Find Var
(c) Use a table of the standard normal probability distribution to approximate P.
Suppose in Problem that the variance of the number of automobiles sold weekly is.
Give a lower bound to the probability that next week’s sales are between and, inclusively.
Give an upper bound to the probability that next week’s sales exceed.
Each new book donated to a library must be processed. Suppose that the time it takes to process a book has a mean of minutes and a standard deviation of minutes. If a librarian has books to process,
(a) approximate the probability that it will take more than minutes to process all these books;
(b) approximate the probability that at least books will be processed in the first minutes. What assumptions have you made?
A lake contains 4 distinct types of fish. Suppose that each fish caught is equally likely to be any one of these types. Let Y denote the number of fish that need be caught to obtain at least one of each type.
(a) Give an interval (a, b) such that
(b) Using the one-sided Chebyshev inequality, how many fish need we plan on catching so as to be at least 90 percent certain of obtaining at least one of each type?
We have components that we will put to use in a sequential fashion. That is, the component is initially put in use, and upon failure, it is replaced by a component, which is itself replaced upon failure by a componentlocalid="1649784865723" , and so on. If the lifetime of component i is exponentially distributed with a mean estimate the probability that the total life of all components will exceed. Now repeat when the life distribution of component i is uniformly distributed over.
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